Abstract: The relation between taxation states and foreign direct
investment has been studied for several perspectives and with states
of different levels of development. Usually it's only considered the
impact of tax level on the foreign direct investment volume. This
paper enhances this view by assuming that multinationals companies
(MNC) can use transfer prices systems and have got investment
timing flexibility. Thus, it evaluates the impact of the use of
international transfer pricing systems on the states- policy and on the
investment timing of the multinational companies. In uncertain
business environments (with periodical release of news), the
investment can increase if MNC detain investment delay options.
This paper shows how tax differentials can attract foreign direct
investments (FDI) and influence MNC behavior. The equilibrium is
set in a global environment where MNC can shift their profits
between states depending on the corporate tax rates. Assuming the
use of transfer pricing schemes, this paper confirms the relationship
between MNC behavior and the release of new business news.
Abstract: The given work is devoted to the description of
Information Technologies NAS of Azerbaijan created and
successfully maintained in Institute. On the basis of the decision of
board of the Supreme Certifying commission at the President of the
Azerbaijan Republic and Presidium of National Academy of
Sciences of the Azerbaijan Republic, the organization of training
courses on Computer Sciences for all post-graduate students and
dissertators of the republic, taking of examinations of candidate
minima, it was on-line entrusted to Institute of Information
Technologies of the National Academy of Sciences of Azerbaijan.
Therefore, teaching the computer sciences to post-graduate
students and dissertators a scientific - methodological manual on
effective application of new information technologies for research
works by post-graduate students and dissertators and taking of
candidate minima is carried out in the Educational Center.
Information and communication technologies offer new
opportunities and prospects of their application for teaching and
training. The new level of literacy demands creation of essentially
new technology of obtaining of scientific knowledge. Methods of
training and development, social and professional requirements,
globalization of the communicative economic and political projects
connected with construction of a new society, depends on a level of
application of information and communication technologies in the
educational process. Computer technologies develop ideas of
programmed training, open completely new, not investigated
technological ways of training connected to unique opportunities of
modern computers and telecommunications. Computer technologies
of training are processes of preparation and transfer of the
information to the trainee by means of computer. Scientific and
technical progress as well as global spread of the technologies
created in the most developed countries of the world is the main
proof of the leading role of education in XXI century. Information
society needs individuals having modern knowledge. In practice, all
technologies, using special technical information means (computer,
audio, video) are called information technologies of education.
Abstract: This study examined the effects of 8-week Pilates training program on limits of stability (LOS) and abdominal muscle strength in young dancers. Twenty-four female volunteered and randomly assigned as experimental group (EG) or control group (CG). All subjects received the same dance lessons but the EG underwent an extra Pilates mat exercises for 40 minutes, three times a week, for 8 weeks. LOS was evaluated by the Biodex Balance System and the abdominal strength was measured by 30/60 seconds sit-ups test. One factor ANCOVA was used to examine the differences between groups after training. The results showed that the overall LOS scores at levels 2/8 and the 30/60 seconds sit-ups for the EG group pre- and post-training were changed from 22/38 % to 31/51 % and 20/33 times to 24/42 times, respectively. The study demonstrated that 8-week Pilates training can improve the LOS performance and abdominal strength in young dancers.
Abstract: The main issue of interest here is whether individuals
who differ in arithmetical reasoning ability and levels of imagery ability display different brain activity during the conduct of mental
arithmetical reasoning tasks. This was a case study of four
participants who represented four extreme combinations of Maths –Imagery abilities: ie., low-low, high-high, high-low, low-high respectively. As the Ps performed a series of 60 arithmetical reasoning tasks, 128-channel EEG recordings were taken and the
pre-response interval subsequently analysed using EGI GeosourceTM
software. The P who was high in both imagery and maths ability
showed peak activity prior to response in BA7 (superior parietal cortex) but other Ps did not show peak activity in this region. The
results are considered in terms of the diverse routes that may be employed by individuals during the conduct of arithmetical reasoning
tasks and the possible implications of this for mathematics education.
Abstract: This paper proposes a new technique based on nonlinear Minmax Detector Based (MDB) filter for image restoration. The aim of image enhancement is to reconstruct the true image from the corrupted image. The process of image acquisition frequently leads to degradation and the quality of the digitized image becomes inferior to the original image. Image degradation can be due to the addition of different types of noise in the original image. Image noise can be modeled of many types and impulse noise is one of them. Impulse noise generates pixels with gray value not consistent with their local neighborhood. It appears as a sprinkle of both light and dark or only light spots in the image. Filtering is a technique for enhancing the image. Linear filter is the filtering in which the value of an output pixel is a linear combination of neighborhood values, which can produce blur in the image. Thus a variety of smoothing techniques have been developed that are non linear. Median filter is the one of the most popular non-linear filter. When considering a small neighborhood it is highly efficient but for large window and in case of high noise it gives rise to more blurring to image. The Centre Weighted Mean (CWM) filter has got a better average performance over the median filter. However the original pixel corrupted and noise reduction is substantial under high noise condition. Hence this technique has also blurring affect on the image. To illustrate the superiority of the proposed approach, the proposed new scheme has been simulated along with the standard ones and various restored performance measures have been compared.
Abstract: Generalized Center String (GCS) problem are
generalized from Common Approximate Substring problem
and Common substring problems. GCS are known to be
NP-hard allowing the problems lies in the explosion of
potential candidates. Finding longest center string without
concerning the sequence that may not contain any motifs is
not known in advance in any particular biological gene
process. GCS solved by frequent pattern-mining techniques
and known to be fixed parameter tractable based on the
fixed input sequence length and symbol set size. Efficient
method known as Bpriori algorithms can solve GCS with
reasonable time/space complexities. Bpriori 2 and Bpriori
3-2 algorithm are been proposed of any length and any
positions of all their instances in input sequences. In this
paper, we reduced the time/space complexity of Bpriori
algorithm by Constrained Based Frequent Pattern mining
(CBFP) technique which integrates the idea of Constraint
Based Mining and FP-tree mining. CBFP mining technique
solves the GCS problem works for all center string of any
length, but also for the positions of all their mutated copies
of input sequence. CBFP mining technique construct TRIE
like with FP tree to represent the mutated copies of center
string of any length, along with constraints to restraint
growth of the consensus tree. The complexity analysis for
Constrained Based FP mining technique and Bpriori
algorithm is done based on the worst case and average case
approach. Algorithm's correctness compared with the
Bpriori algorithm using artificial data is shown.
Abstract: Broccoli has been widely recognized as a wealthy
vegetable which contains multiple nutrients with potent anti-cancer
properties. Lamb’s lettuce has been used as food for many centuries
but only recently became commercially available and literature is
therefore exiguous concerning these vegetables. The aim of this work
was to evaluate the influence of the extraction conditions on the yield
of phenolic compounds and the corresponding antioxidant capacity of
broccoli and lamb’s lettuce. The results indicate that lamb’s lettuce,
compared to broccoli, contains simultaneously a large amount of total
polyphenols as well as high antioxidant activity. It is clearly
demonstrated that extraction solvent significantly influences the
antioxidant activity. Methanol is the solvent that can globally
maximize the antioxidant extraction yield. The results presented
herein prove lamb’s lettuce as a very interesting source of
polyphenols, and thus a potential health-promoting food.
Abstract: In Virtual organization, Knowledge Discovery (KD)
service contains distributed data resources and computing grid nodes.
Computational grid is integrated with data grid to form Knowledge
Grid, which implements Apriori algorithm for mining association
rule on grid network. This paper describes development of parallel
and distributed version of Apriori algorithm on Globus Toolkit using
Message Passing Interface extended with Grid Services (MPICHG2).
The creation of Knowledge Grid on top of data and
computational grid is to support decision making in real time
applications. In this paper, the case study describes design and
implementation of local and global mining of frequent item sets. The
experiments were conducted on different configurations of grid
network and computation time was recorded for each operation. We
analyzed our result with various grid configurations and it shows
speedup of computation time is almost superlinear.
Abstract: The Wind Turbine Modeling in Wind Energy Conversion System (WECS) using Doubly-Fed Induction Generator (DFIG) PI Controller based design is presented. To study about the variable wind speed. The PI controller performs responding to the dynamic performance. The objective is to study the characteristic of wind turbine and finding the optimum wind speed suitable for wind turbine performance. This system will allow the specification setting (2.5MW). The output active power also corresponding same the input is given. And the reactive power produced by the wind turbine is regulated at 0 Mvar. Variable wind speed is optimum for drive train performance at 12.5 m/s (at maximum power coefficient point) from the simulation of DFIG by Simulink is described.
Abstract: For scores of years now, several microfinance
organizations, non governmental organizations and other welfare
organizations have, with a view to aiding the progress of
communities rooted in poverty have been focusing on creating
microentrepreneurs, besides taking several other measures. In recent
times, business corporations have joined forces to combat poverty by
taking up microenterprise development. Hindustan Unilever Limited
(HUL), the Indian subsidiary of Unilever Limited exemplifies this
through its Project Shakti. The company through the Project creates
rural women entrepreneurs by making them direct to home sales
distributors of its products in villages that have thus far been ignored
by multinational corporations. The members participating in Project
Shakti are largely self help group members. The paper focuses on
assessing the impact made by the company on the members engaged
in Project Shakti. The analysis involves use of quantitative methods
to study the effect of Project Shakti on those self help group
members engaged in Project Shakti and those not engaged with
Project Shakti. Path analysis has been used to study the impact made
on those members engaged in Project Shakti. Significant differences
were observed on fronts of entrepreneurial development, economic
empowerment and social empowerment between members associated
with Project Shakti and those not associated with Project Shakti.
Path analysis demonstrated that involvement in Project Shakti led to
entrepreneurial development resulting in economic empowerment
that in turn led to social empowerment and that these three elements
independently induced a feeling of privilege in the women for being
associated with the Project.
Abstract: Signature represents an individual characteristic of a
person which can be used for his / her validation. For such application
proper modeling is essential. Here we propose an offline signature
recognition and verification scheme which is based on extraction of
several features including one hybrid set from the input signature
and compare them with the already trained forms. Feature points
are classified using statistical parameters like mean and variance.
The scanned signature is normalized in slant using a very simple
algorithm with an intention to make the system robust which is
found to be very helpful. The slant correction is further aided by the
use of an Artificial Neural Network (ANN). The suggested scheme
discriminates between originals and forged signatures from simple
and random forgeries. The primary objective is to reduce the two
crucial parameters-False Acceptance Rate (FAR) and False Rejection
Rate (FRR) with lesser training time with an intension to make the
system dynamic using a cluster of ANNs forming a multiple classifier
system.
Abstract: The purposes of this research are 1) to study English language learning strategies used by the fourth-year students majoring in English and Business English, 2) to study the English language learning strategies which have an affect on English learning achievement, and 3) to compare the English language learning strategies used by the students majoring in English and Business English. The population and sampling comprise of 139 university students of the Suan Sunandha Rajabhat University. Research instruments are language learning strategies questionnaire which was constructed by the researcher and improved on by three experts and the transcripts that show the results of English learning achievement. The questionnaire includes 1) Language Practice Strategy 2)Memory Strategy 3) Communication Strategy 4)Making an Intelligent Guess or Compensation Strategy 5) Self-discipline in Learning Management Strategy 6) Affective Strategy 7)Self-Monitoring Strategy 8) Self-studySkill Strategy. Statistics used in the study are mean, standard deviation, T-test and One Way ANOVA, Pearson product moment correlation coefficient and Regression Analysis. The results of the findings reveal that the English language learning strategies most frequently used by the students are affective strategy, making an intelligent guess or compensation strategy, self-studyskill strategy and self-monitoring strategy respectively. The aspect of making an intelligent guess or compensation strategy had the most significant affect on English learning achievement. It is found that the English language learning strategies mostly used by the Business English major students and moderately used by the English major students. Their language practice strategies uses were significantly different at the 0.05 level and their communication strategies uses were significantly different at the 0.01 level. In addition, it is found that the poor students and the fair ones most frequently used affective strategy while the good ones most frequently used making an intelligent guess or compensation strategy. KeywordsEnglish language, language learning strategies, English learning achievement, and students majoring in English, Business English. Pranee Pathomchaiwat is an Assistant Professor in Business English Program, Suan Sunandha Rajabhat University, Bangkok, Thailand (e-mail: [email protected]).
Abstract: One promising way to achieve low temperature
combustion regime is the use of a large amount of cooled EGR. In
this paper, the effect of injection timing on low temperature
combustion process and emissions were investigated via three
dimensional computational fluid dynamics (CFD) procedures in a DI
diesel engine using high EGR rates. The results show when
increasing EGR from low levels to levels corresponding to reduced
temperature combustion, soot emission after first increasing, is
decreased beyond 40% EGR and get the lowest value at 58% EGR
rate. Soot and NOx emissions are simultaneously decreased at
advanced injection timing before 20.5 ºCA BTDC in conjunction
with 58% cooled EGR rate in compared to baseline case.
Abstract: Although current competitive challenges induced by today-s digital economy place their main emphasis on organizational knowledge, customer knowledge has been overlooked. On the other hand, the business community has finally begun to realize the important role customer knowledge can play in the organizational boundaries of the corporate arena. As a result, there is an emerging market for the tools and utilities whose objective is to provide the intelligence for knowledge sharing between the businesses and their customers. In this paper, we present a conceptual model of customer knowledge management by identifying and analyzing the existing tools in the market. The focus will be upon the emerging British dotcom industry whose customer based B2C behavior has been an influential part of the knowledge based intelligence tools in existence today.
Abstract: Quality evaluation of urban environment is an integral
part of efficient urban environment planning and management. The
development of fuzzy set theory (FST) and the introduction of FST
to the urban study field attempts to incorporate the gradual variation
and avoid loss of information. Urban environmental quality
assessment pertain to interpretation and forecast of the urban
environmental quality according to the national regulation about the
permitted content of contamination for the sake of protecting human
health and subsistence environment . A strategic motor vehicle
control strategy has to be proposed to mitigate the air pollution in the
city. There is no well defined guideline for the assessment of urban
air pollution and no systematic study has been reported so far for
Indian cities. The methodology adopted may be useful in similar
cities of India. Remote sensing & GIS can play significant role in
mapping air pollution.
Abstract: The paper deals with an analysis of visibility records collected from 210 European airports to obtain a realistic estimation of the availability of Free Space Optical (FSO) data links. Commercially available optical links usually operate in the 850nm waveband. Thus the influence of the atmosphere on the optical beam and on the visible light is similar. Long-term visibility records represent an invaluable source of data for the estimation of the quality of service of FSO links. The model used characterizes both the statistical properties of fade depths and the statistical properties of individual fade durations. Results are presented for Italy, France, and Germany.
Abstract: Self-organizing map (SOM) is a well known data reduction technique used in data mining. Data visualization can reveal structure in data sets that is otherwise hard to detect from raw data alone. However, interpretation through visual inspection is prone to errors and can be very tedious. There are several techniques for the automatic detection of clusters of code vectors found by SOMs, but they generally do not take into account the distribution of code vectors; this may lead to unsatisfactory clustering and poor definition of cluster boundaries, particularly where the density of data points is low. In this paper, we propose the use of a generic particle swarm optimization (PSO) algorithm for finding cluster boundaries directly from the code vectors obtained from SOMs. The application of our method to unlabeled call data for a mobile phone operator demonstrates its feasibility. PSO algorithm utilizes U-matrix of SOMs to determine cluster boundaries; the results of this novel automatic method correspond well to boundary detection through visual inspection of code vectors and k-means algorithm.
Abstract: In a pilot plant scale of a fluidized bed reactor, a
reduction reaction of sodium sulfate by natural gas has been
investigated. Natural gas is applied in this study as a reductant. Feed
density, feed mass flow rate, natural gas and air flow rate
(independent parameters)and temperature of bed and CO
concentration in inlet and outlet of reactor (dependent parameters)
were monitored and recorded at steady state. The residence time was
adjusted close to value of traditional reaction [1]. An artificial neural
network (ANN) was established to study dependency of yield and
carbon gradient on operating parameters. Resultant 97% accuracy of
applied ANN is a good prove that natural gas can be used as a
reducing agent. Predicted ANN model for relation between other
sources carbon gradient (accuracy 74%) indicates there is not a
meaningful relation between other sources carbon variation and
reduction process which means carbon in granule does not have
significant effect on the reaction yield.
Abstract: This paper presents the results of corrosion fatigue
crack growth behaviour of a Ni-Cr-Mn steel commonly used in
marine applications. The effect of mechanical variables such as
frequency and load ratio on fatigue crack growth rate at various
stages has been studied using compact tension (C(T)) specimens
along the rolling direction of steel plate under 3.5% saturated NaCl
aqueous environment. The significance of crack closure on corrosion
fatigue, and the validity of Elber-s empirical linear crack closure
model with the ASTM compliance offset method have been
examined.
Fatigue crack growth rate is higher and threshold stress intensities
are lower in aqueous environment compared to the lab air conditions.
It is also observed that the crack growth rate increases at lower
frequencies. The higher stress ratio promotes the crack growth. The
effect of oxidization and corrosion pit formation is very less as the
stress ratio is increased. It is observed that as stress ratios are
increased, the Elber-s crack closure model agrees well with the crack
closure estimated by the ASTM compliance offset method for tests
conducted at 5Hz frequency compared to tests conducted at 1Hz in
corrosive environment.
Abstract: Matching algorithms have significant importance in
speaker recognition. Feature vectors of the unknown utterance are
compared to feature vectors of the modeled speakers as a last step in
speaker recognition. A similarity score is found for every model in
the speaker database. Depending on the type of speaker recognition,
these scores are used to determine the author of unknown speech
samples. For speaker verification, similarity score is tested against a
predefined threshold and either acceptance or rejection result is
obtained. In the case of speaker identification, the result depends on
whether the identification is open set or closed set. In closed set
identification, the model that yields the best similarity score is
accepted. In open set identification, the best score is tested against a
threshold, so there is one more possible output satisfying the
condition that the speaker is not one of the registered speakers in
existing database. This paper focuses on closed set speaker
identification using a modified version of a well known matching
algorithm. The results of new matching algorithm indicated better
performance on YOHO international speaker recognition database.